NiO-TiO2 p-n Heterojunction for Solar Hydrogen Generation
Bibliographic record
Abstract
Photocatalytic water splitting for hydrogen production has been widely recognized as a promising strategy for relieving the pressure from energy crisis and environmental pollution. However, current efficiency for photocatalytic hydrogen generation has been limited due to a low separation of photogenerated electrons and holes. p-n heterojunction with a built-in electric field emerges as an efficient strategy for photocatalyst design to boost hydrogen evolution activities due to a spontaneous charge separation. In this work, we investigated the effect of different preparation methods on photocatalytic hydrogen production over NiO-TiO2 composites. The results demonstrated that a uniform distribution of NiO on a surface of TiO2 with an intimate interfacial interaction was formed by a sol-gel method, while direct calcination tended to form aggregation of NiO, thus leading to an uneven p-n heterojunction structure within a photocatalyst. NiO-TiO2 composites fabricated by different methods showed enhanced hydrogen production (23.5 ± 1.2, 20.4 ± 1.0 and 8.8 ± 0.7 mmolh−1g−1 for S1-20%, S2-20% and S3-10%, respectively) as compared with pristine TiO2 (6.6 ± 0.7 mmolh−1g−1) and NiO (2.1 ± 0.2 mmolh−1g−1). The current work demonstrates a good example to improve photocatalytic hydrogen production by finely designing p-n heterojunction photocatalysts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".